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Dr. ir. Ann van GriensvenDepartment of Hydroinformatics and Knowledge ManagementUNESCO-IHE, the Netherlands
Soil and Water Assessment Tool (SWAT)
Course objectives
Get familiar with SWATWhat are the key processes, key parameters?What are the main application domains?
How can we set up a model (get a bit a feeling)?What are the main data needed?
SWATDeveloped by Jeff Arnold at USDA/ARS Temple, Texas, USAGIS interface (ArcView): DEM, Landuse, Soils maps Open sourcesUser and developers communityswatmodel.tamus.edu
What are the objectives of SWATSimulation of processes at land and water phaseSpatially distributed (different scales)Semi physically based / empirical approachesSimulation of changes (climate, land use, management etc.)Water quantities, incl. different runoff componentsWater quality: Nutrients, Sediments, Pesticides, Bacteria, (algae and oxygen), etc.
…. all that on a daily time step and at different spatial scales and (more or less) readily available data sets!!
wwwhttp://swatmodel.tamus.edu/
Download softwareDownload source code
DocumentationUser group mailing list !
Internet Forum
PublicationsApplications
Philosophy (1)Aims
Management analysisWater, sediments, crops, nutrients,
pesticides
Comprehensive –
Process Interactions
InputReadily available input
Physically based input
Philosophy (2)
• Semi-distributed model Conceptual model
Long term simulationsContinuous Time – Daily/hourly time step
Problem of computational efficiency
BasinSubbasins
Weather, RoutingHydrological Response Units
= Combination of soil type and land use properties
Structure
HRU (2)
NOT
GEO -
REFERENCED
Totaloutput
+
Output 1 x A x 6
Output 2 x A x 5
Output 3 x A x 8
Output 4 x A x 1
HRU6
581
1
2
3
4
# of pixels
input Output 1
input Output 2
input Output 3
input Output 4
1 unit area
SWAT
SWAT DATABASESHRU parameters
GIS subbasin
Pixels : 20Pixel area = A
GEO -
REFERENCED
ARCVIEW
HRU’s in model
Created on the basis of Land Use maps and Soil Maps + databases (with parameters)!!!
Soil map ↔ lookup table ↔ usersoil.dbf (swat2005.mdb)Land use map ↔ lookup table ↔ crop.dbf (swat2005.mdb)Slope classes (drived from DEM)
Root Zone
Shallow (unconfined)
Aquifer
Vadose(unsaturated)
Zone
Confining Layer
Deep (confined)
Aquifer
PrecipitationEvaporation and
Transpiration
Infiltration/plant uptake/ Soil moisture redistribution
Surface RunoffLateral Flow
Return FlowRevap from
shallow aquiferPercolation to
shallow aquifer
Recharge to deep aquifer
Flow out of watershed
Hydrologic Balance
How is SWAT solving the problems?
Curve Number Values (many more can be found in the manual)
Soil group Land use
% imper-vious A B C D
Residential 20 51 68 79 84 25 54 70 80 85 30 57 72 81 86 38 61 75 83 87 65 77 85 90 92 Parking, roads, rofs 100 98 98 98 98 Cobbles - 76 85 89 91 Commercia 85 89 92 94 95 Industria 72 81 88 91 93 Open ( park, grass...) > 75% grass cover - 39 61 74 80 50 tot 75% grass cover - 49 69 79 84 Meadow - 30 58 71 78 Woods Open - 45 66 77 73 Dense - 25 55 70 77 Agricultural land - 62 71 78 81
10) - CN
1000( 25.4 = S
1) Wetness condition 2
2) 5 % slopeEmpirical equations exist to adjust for different slopes
Key parameter!
Curve Number Value VariationsSoil Groups
Wetness conditions
ABCD
Deep sand, deep loess (low runoff potential)Sandy loam, shallow loess (low to moderate runoff potential)Clay-loam, shallow sandy loam (moderate to high runoff potential)Heavy plastic clay, swelling soil, silty soil (high runoff potential)
CN1CN2CN3
Dry but above wilting pointAverageAbove field capacity, near saturation
Empirical equations exists to calculate CN1 and CN3 from CN2
Subsurface flow
Upper soil layers
ShallowaquiferDeep
aquifer
lateral flowpercolation
infiltration
return flowloss
Erosion
Modified Universal Soil Loss Equation (MUSLE)
V = surface qp = is the peak flow rate K = erodibility factorC = crop management factorPE = the erosion control practice factorLS = slope length and steepness factor.
(LS) (PE) (C) (K) )q (V 11.8 = Y 0.56p
NO3- NH4
+
Soil Organic Matter
NO2-
manures, wastes and sludge
ammonium fixationclay
mineralization
immobilization
nitrification
immobilization
Symbiotic fixation
NO3-
anaerobicconditions
N2 N2 O
NH3Atmospheric N fixation
leaching
fertilizer fertilizer
Harvest
denitrification
ammonia volatilization
runoff
Nitrogen Cycle
Soil Organic Matter
H2 PO4-
HPO4-2
manures, wastes and sludge
mineralization
immobilization
fertilizer Harvest
manures, wastes, and sludge
Adsorbed and fixedInorganic
Fe, Al, Ca, and clay
runoff
Phosphorous Cycle
Foliar Application
Degradation
Washoff
Infiltration
Leaching
Runoff
Surface Application
Degradation
Pesticide dynamics
Agricultural management (1)
Crop RotationsRemoval of Biomass as HarvestConversion of Biomass to ResidueTillage / Biomixing of Soil Fertilizer Applications GrazingPesticide ApplicationsFilter strips
DataWeather data
RainfallRaingage and RADAR
Temperature
Landuse dataRemote Sensing
Land management
Soils and its attributes
Streamflow (quantity)
Water quality
Databases in swat2005.mbd• Soil• Land cover / plant growth• Tillage• Fertilizer• Pesticide• Urban• Weather generator
Data preparation (1)
GIS maps:DTMLand useSoil
Databases (in swat2005.mdb)Userwgn.dbfUsersoil.dbfCrop.dbf -> create crop.dat
Data preparation (2)
Lookup tablesFor soilFor land use
Soil map ↔ lookup table ↔ usersoil.dbfLand use map ↔ lookup table ↔ crop.dbf
Data preparation (3)
Rainfall dataTable with station names and locations (batch files)Data file for each station
Temperature dataTable with station names and locationsData file for each station
Data preparation (4)
Climate stationsTable with station names and locations (batch file)Userwgn.dbf with data for each station
Userwgn.dbf (long term climatic condition)
Rainfall Statistical parameters derivation
Use pcpSTAT.exeUse ASCII text file format to create Input file (e.g. R002.txt)The line of input data file must be a blankOne column of rainfall data valuesThe record should start Jan 1 and End Dec. 31The missing rainfall values should be assigned -99.0
The outputs (e.g. R002.out)File 1 R002.out: Statistical Analysis of Daily Precipitation data. Directly used in userwgn.dbfFile 2 mean_pcp.st: Average Daily precipitation in MonthFile 3 totalpcp.sta: Total Monthly precipitation
Subbasin:
Input.sub: subbasin (area,…).wgn: weather information (#gage or generate).wus: water use.pnd: pond
Output: output.sub
#
#
##
##
####
###### ##
##
#
#
#
#
3
21
17
20
21
8
7
4
5
10
69
13
1816
12
2219
14
11
15
HRU:
Input.hru: HRU information (area,…).sol: sol data.chm: chemical composition soils.gw: groundwater.mgt: agricultural management (Curve number!)
Output: output.hru
River routing:
Input:.rte: river routing input (morphology, manning, …).swq: stream water quality
Output: output.rte
SWAT i/o files:
../Project/scenarios/default/sim#/txtinout
../Project/scenarios/default/sim#/tablesin
../Project/scenarios/default/sim#/tablesout
Dr. ir. Ann van GriensvenDepartment of Hydroinformatics and Knowledge ManagementUNESCO-IHE, the Netherlands
Dr. Preksedis .M. NdombaDepartment of Water Resources EngineeringUNIVERSITY OF DAR ES SALAAM, TANZANIA
The use of SWAT within the Nile Basin
Pangani River Basin (Ndomba)
0
50
100
150
200
250
1976
1977
1978
1979
1980
1981
1982
Stre
amflo
w (m
3/s)
obseved simulated
020
4060
80100
120140
160
Aug-76
Jan-78
May-79
Oct-80
Feb-82
Jul-83St
ream
flow
(m3/
s)Observed Simulated
0
50
100
150
200
250
0 100 200Observed streamflow (m3/s)
Est
imat
ed st
ream
flow
(m3/
s)
0
50
100
150
200
250
300
0 20 40 60 80 100
Percent of time discharge is equalled or exceeded
Stre
amflo
w (m
3/s)
Observed Estimated
0
20
40
60
80
100
120
140
02/01/1970
01/07/1970
28/12/1970
26/06/1971
23/12/1971
20/06/1972
17/12/1972
Stre
amflo
w (m
3/s)
Observed Estimated
0
5
10
15
20
25
30
35
40
45
1983
1986
1989
1992
1995
1998
2001
2004
Ave
rage
ann
ual f
low
(m3/
s)
Observed Estimated
Daily
R2=54.6%
Monthly
R2=65%
Annually IVF=100%
Validation, R2=68%
Lake Tana
-3.99- -3
-2.99 - -2
-1.99- -1
-0.99 - -0.50
-0.5 - 0.5
0.5 - 1
1 - 2
2 - 3
SMDI Jan, 2005
Lake T
-3.99-
-2.99 -
Drought indexes: upper Blue Nile
Slide by Rahel Tessema
Water resources managament... Jurgen Schuol & Karim Abbaspour
Blue water
Green water flow
Slide by Jurgen Schuol
Kirumi wetlandImportant part of ecosystem, supports lives of about 6000 peopleSituated on the lower end of the catchmentIt is important to include the wetland in the EFA process
Kirumi wetland
Environmental Flow: Mara catchmentSlide by Florence Mahay